Predicting Postoperative Hospital Stay in Neurosurgery with Recurrent Neural Networks Based on Operative Reports

This study aimed to predict the duration of the postoperative in-hospital period in neurosurgery based on unstructured operative reports, natural language processing, and deep learning. The recurrent neuronal network (RNN-GRU) was tuned on the word-embedded reports of primary surgical cases retrieved for the period between 2000 and 2017. A new test dataset obtained for the primary operations performed in 2018-2019 was used to evaluate model performance. The mean absolute error of prediction in the final test was 3.00 days. Our study demonstrated the usability of textual EHRs data for the prediction of postoperative period length in neurosurgery using deep learning.